A System Aware Resource Allocation for Distributed Workflows in Quantum Computing Environments

TL;DR

This paper presents a resource allocation system for distributed quantum workflows that optimizes device assignment considering cost metrics, improving efficiency and fidelity over existing methods.

Contribution

It introduces a comprehensive allocation framework for distributed quantum workflows, incorporating cost metrics and modified graph algorithms for better resource utilization.

Findings

Achieves approximately 5% reduction in execution time

Reduces communication overhead by about 30%

Improves fidelity by 2% on average

Abstract

Rapid advancements in cloud based platforms providing access to quantum computing capabilities have opened up several challenges for efficient usage of these highly delicate and costly devices. Although most of the current systems use a priority based access protocol, they are unable to fully support reliable, efficient, and scalable execution of larger-scale applications. To overcome this limitation, we propose a comprehensive solution for efficient allocation of quantum programs to appropriate quantum devices, considering all the relevant cost metrics into account including, fidelity, execution time and communication overhead. We also formulate use-cases for distributed quantum workflow and propose modified graph based algorithms to solve for allocation of such use-cases, assuming a hybrid classical-quantum network. Since hardware advancements in large standalone devices is an ongoing process, it is critical to investigate such distributed workflows to maximize the best utilization of current NISQ devices. Our empirical study shows that the proposed techniques perform better than state-of-the-art methods for almost all evaluation parameters, with average improvements of approximately $5\%$ in execution time, $30\%$ in communication overhead, $40\%$ in wait time and $2\%$ in fidelity, providing better solutions to efficient allocation strategies.